Results 61 to 70 of about 14,178 (228)
IET Control Theory &Applications, Volume 20, Issue 1, January/December 2026.This study presents a novel deep learning‐based fault classification framework utilising Variational Mode Decomposition (VMD) for adaptive feature extraction and a Multi‐branch Convolutional Neural Network (M1D‐CNN) architecture for classification. The VMD hyperparameters were optimised based on kurtosis to ensure the extraction of the most informative
Seyyid Ahmed Djellouli +4 more
wiley +1 more source
RESEARCH ON FAULT DIAGNOSIS OF WIND TURBINE PLANETARY GEARBOX UNDER VARIABLE SPEED
Jixie qiangdu, 2022 Due to the nonstationarity, complex transmission path, high system noise and serious modulation phenomenon of wind turbine gearbox vibration signal, the conventional spectrum analysis method was difficult to identify the fault location of gearbox.
CUI Cheng +3 more
doaj
IET Renewable Power Generation, Volume 20, Issue 1, January/December 2026.This study presents an automated approach for wind turbine fault diagnosis by integrating deep learning with an optimized gradient boosting model to address imbalanced SCADA data. Using t‐SNE representations and deep features from a physics‐informed CNN, the method enhances fault classification, while AEPSO optimizes a CatBoost classifier.
Chun‐Yao Lee +2 more
wiley +1 more source
Jixie chuandong, 2009 Wind turbine gearbox is a large complex parts of wind turbine,the normal work of gears in gearbox can be affected by the intensity of gearbox directly.For the first domestic 2.5MW wind turbine,its three-dimensional model is finished.On the basis of ...
陈毅, 侯力, 马朝玲, 蒋苏民
doaj
Interpretable Multi‐Turbine Output Prediction of Offshore Wind Farms Based on FAGTTN Model
IET Renewable Power Generation, Volume 20, Issue 1, January/December 2026.This paper proposes a power prediction model feature attention graph convolutional neural network with temporal transformers (FAGTTN) for offshore wind farms based on the feature attention module, adaptive graph convolutional neural network (AGCN) and temporal transformers.
Xiangjing Su +5 more
wiley +1 more source
Jixie chuandong, 2018 Due to the large size and weight of large wind turbine gearbox,its statics characteristic and gear contact characteristic are different under different supporting method.
Ji Kefeng, Zhang Shijie
doaj
Investigations on the performances of the electrical generator of a rim-driven marine current turbine” [PDF]
, 2014 In this paper, the electrical generator of a rim-driven horizontal-axis current turbine is modeled in detail. Its main characteristics and performances are evaluated (efficiency, mass, cost, etc).
CHARPENTIER, Jean-Frederic +3 more
core +1 more source
Comparison of multiple stage braking circuits for wind driven generators [PDF]
, 2016 This paper presents multiple stage braking circuits for wind turbines with a permanent magnet synchronous generator. The system combines both passive converter circuit coupled to a resistive braking circuit.
Valchev, Vencislav Cekov +2 more
core +1 more source
Detection of natural crack in wind turbine gearbox [PDF]
Renewable Energy, 2018 Abstract One of the most challenging scenarios in bearing diagnosis is the extraction of fault signatures from within other strong components which mask the vibration signal. Usually, the bearing vibration signals are dominated by those of other components such as gears and shafts.
Suliman Shanbr +3 more
openaire +3 more sources
IET Renewable Power Generation, Volume 20, Issue 1, January/December 2026.This study introduces a novel framework integrating distributed sensor networks with advanced machine learning, utilising physics‐informed neural networks (PINNs) to enhance predictive maintenance and performance optimisation for wind turbines and solar farms, achieving an 87% failure prediction accuracy with a 14‐day lead time.
Nasir Muhamad +5 more
wiley +1 more source